code: def setUp(self):
      if self.activ == "relu":
          activ = relu
      elif self.activ == "add_one":
          activ = _add_one
      elif self.activ is None:
          activ = None
      self.x = np.random.uniform(
          -1, 1, (5, self.in_channels, 5, 5)
      ).astype(np.float32)
      self.gy = np.random.uniform(
          -1, 1, (5, self.out_channels, 5, 5)
      ).astype(np.float32)
  
      # Convolution is the identity function.
      dw_initialW = np.array(
          [[0, 0, 0], [0, 1, 0], [0, 0, 0]] * self.in_channels,
          dtype=np.float32,
      ).reshape((self.in_channels, 1, 3, 3))
      pw_initialW = np.eye(
          self.in_channels, self.out_channels, dtype=np.float32
      ).reshape((self.out_channels, self.in_channels, 1, 1))
      bn_kwargs = {"decay": 0.8}
      self.l = SeparableConv2DBNActiv(
          self.in_channels,
          self.out_channels,
          self.ksize,
          self.stride,
          self.pad,
          self.dilate,
          dw_initialW=dw_initialW,
          pw_initialW=pw_initialW,
          dw_activ=activ,
          pw_activ=None,
          bn_kwargs=bn_kwargs,
      )
  
file_path: chainercv/tests/links_tests/connection_tests/test_separable_conv_2d_bn_activ.py
imports: import unittest
  import chainer
  from chainer.backends import cuda
  from chainer.functions import relu
  from chainer import testing
  from chainer.testing import attr
  from chainercv.links import SeparableConv2DBNActiv
  import numpy
label_desc: Use image node_id 1 for calling the TestSeparableConv2DBNActiv obj's underlying member method code with example usage: obj.setUp() without return types